diff --git a/Dockerfile b/Dockerfile
index 18611113b..c35c8c8b8 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -102,5 +102,6 @@ RUN (apt-get autoremove -y; \
 WORKDIR /opt/frigate/
 ADD frigate frigate/
 COPY detect_objects.py .
+COPY benchmark.py .
 
 CMD ["python3", "-u", "detect_objects.py"]
diff --git a/benchmark.py b/benchmark.py
new file mode 100644
index 000000000..4ef1fe9de
--- /dev/null
+++ b/benchmark.py
@@ -0,0 +1,20 @@
+import statistics
+import numpy as np
+from edgetpu.detection.engine import DetectionEngine
+
+# Path to frozen detection graph. This is the actual model that is used for the object detection.
+PATH_TO_CKPT = '/frozen_inference_graph.pb'
+
+# Load the edgetpu engine and labels
+engine = DetectionEngine(PATH_TO_CKPT)
+
+frame = np.zeros((300,300,3), np.uint8)
+flattened_frame = np.expand_dims(frame, axis=0).flatten()
+
+detection_times = []
+
+for x in range(0, 1000):
+    objects = engine.DetectWithInputTensor(flattened_frame, threshold=0.1, top_k=3)
+    detection_times.append(engine.get_inference_time())
+
+print("Average inference time: " + str(statistics.mean(detection_times)))
\ No newline at end of file